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InSAR Water Vapor Data Assimilation into Mesoscale Model MM5: Technique and Pilot Study

TitoloInSAR Water Vapor Data Assimilation into Mesoscale Model MM5: Technique and Pilot Study
Tipo di pubblicazioneArticolo su Rivista peer-reviewed
Anno di Pubblicazione2015
AutoriPichelli, Emanuela, Ferretti Rossella, Cimini Domenico, Panegrossi Giulia, Perissin Daniele, Pierdicca Nazzareno, Rocca Fabio, and Rommen Bjorn
RivistaIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume8
Paginazione3859 – 3875
Type of ArticleArticle
ISSN19391404
Abstract

In this study, a technique developed to retrieve integrated water vapor from interferometric synthetic aperture radar (InSAR) data is described, and a three-dimensional variational assimilation experiment of the retrieved precipitable water vapor into the mesoscale weather prediction model MM5 is carried out. The InSAR measurements were available in the framework of the European Space Agency (ESA) project for the "Mitigation of electromagnetic transmission errors induced by atmospheric water vapor effects" (METAWAVE), whose goal was to analyze and possibly predict the phase delay induced by atmospheric water vapor on the spaceborne radar signal. The impact of the assimilation on the model forecast is investigated in terms of temperature, water vapor, wind, and precipitation forecast. Changes in the modeled dynamics and an impact on the precipitation forecast are found. A positive effect on the forecast of the precipitation is found for structures at the model grid scale or larger (1 km), whereas a negative effect is found on convective cells at the subgrid scale that develops within 1 h time intervals. The computation of statistical indices shows that the InSAR assimilation improves the forecast of weak to moderate precipitation (<15 mm/3 h). © 2008-2012 IEEE.

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Cited by: 51

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84941915317&doi=10.1109%2fJSTARS.2014.2357685&partnerID=40&md5=70d42fd4ebb241d1d8bf556d1f74fcdd
DOI10.1109/JSTARS.2014.2357685
Citation KeyPichelli20153859